Triple

T23818743
Position Surface form Disambiguated ID Type / Status
Subject Ellen Kuzwayo E589169 entity
Predicate notableWork P4 FINISHED
Object Sit and Listen, Beloved
"Sit and Listen, Beloved" is a reflective work by South African activist and writer Ellen Kuzwayo that explores Black women's experiences under apartheid and the importance of storytelling across generations.
 E1606741 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Sit and Listen, Beloved | Statement: [Ellen Kuzwayo, notableWork, Sit and Listen, Beloved]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Sit and Listen, Beloved
Triple: [Ellen Kuzwayo, notableWork, Sit and Listen, Beloved]
Generated description
"Sit and Listen, Beloved" is a reflective work by South African activist and writer Ellen Kuzwayo that explores Black women's experiences under apartheid and the importance of storytelling across generations.

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69e25d18619081909c7fb89d8926f14a completed April 17, 2026, 4:17 p.m.
NER Named-entity recognition batch_69f1c7ad0ec88190bace5c3f00908b30 completed April 29, 2026, 8:56 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f6986c1c88190b2ad7cac4c9db05c completed May 21, 2026, 8:22 p.m.
NEDg Description generation batch_6a0f6d3f59308190a05f96b74183c51f completed May 21, 2026, 8:38 p.m.
NED2 Entity disambiguation (via description) batch_6a0f6dc831c08190b55834bbdd1d85a3 completed May 21, 2026, 8:40 p.m.
Created at: April 17, 2026, 7:58 p.m.